UAVs Trajectory Planning by Distributed MPC under Radio Communication Path Loss Constraints

Grancharova, Alexandra; Grøtli, Esten Ingar; Ho, Tu Dac; Johansen, Tor Arne

doi:10.1007/s10846-014-0090-1

Cited by 55 publications

(21 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the signal can vary (fade), for example, due to shadowing from obstacles or due to multipath propagation. Fading may be modeled, for example, as Rayleigh fading (more appropriate for heavily built‐up urban environments), Rician fading (if line‐of‐sight communication dominates), or Nakagami‐

m

fading . Therefore, drone positioning as a flying base station depends on signal fading along the communication path, path loss, interferences, and noise.…”

Section: Characteristics Of Drones Relevant To Operational Planningmentioning

confidence: 99%

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

et al. 2018

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult‐to‐access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

show abstract

m

fading . Therefore, drone positioning as a flying base station depends on signal fading along the communication path, path loss, interferences, and noise.…”

Section: Characteristics Of Drones Relevant To Operational Planningmentioning

confidence: 99%

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

et al. 2018

View full text Add to dashboard Cite

show abstract

“…We proceed to do so for the dynamics used for UAV path planning in Grøtli and Johansen [2012], Grancharova et al [2014] of the form (19):…”

Section: Mpc Implementationmentioning

confidence: 99%

On corner cutting in multi-obstacle avoidance problems

Stoican¹,

Grøtli

Prodan

et al. 2015

IFAC-PapersOnLine

View full text Add to dashboard Cite

Abstract:One challenging and not extensively studied issue in obstacle avoidance is the corner cutting problem. Avoidance constraints are usually imposed at the sampling time without regards to the intra-sample behavior of the dynamics. This paper improves upon state of the art by describing a multi-obstacle environment over a hyperplane arrangement scaffolding, provides a piecewise description of the "shadow" regions and represents them into a combined mixed integer and predictive control formulation. Furthermore, over-approximation constraints which reduce to strictly binary formulations are discussed in detail. Illustrative proofs of concept, comparisons with the state of the art and simulation results over a classical multi-obstacle avoidance problem validate the benefits of the proposed approach.

show abstract

“…For example, in [44], a distributed linear MPC approach was implemented to solve the trajectory planning problem for rotary wing UAVs, with an objective to form a communication network of multiple targets. In this case, the UAV model was a linear relation between position and velocity, while the attitude of the UAV was not considered and thus the authors did not consider the nonlinear behavior of the UAV.…”

Section: A Related Workmentioning

confidence: 99%

“…Few of them utilized a three dimensional space but the authors used a simple linear model or did not consider the attitude problem of the UAV ( [44], [46], [48]). In general, only few works considered the nonlinear model in a three dimensional space but still the authors, in this approaches have not considered cooperation strategies and focused only on one UAV control problem ( [41], [42], [43]and [45]).…”

Section: A Related Workmentioning

confidence: 99%

Distributed model predictive control for unmanned aerial vehicles

Mansouri

Nikolakopoulos

Gustafsson

2015

2015 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS)

View full text Add to dashboard Cite

Abstract-In this article a distributed model predictive control scheme, for the cooperative motion control of Unmanned Aerial Vehicles (UAVs) is being presented. The UAVs are modeled by a 6-DOF nonlinear kinematic model. Two di↵erent control architectures: a centralized and a distributed MPC, are studied and evaluated in simulation experiments. In the centralized approach, one central MPC controller is responsible for the movement coordination of all the UAVs, while in the distributed approach each aerial vehicle plans only for its own actions, while the objective function is coupled with the behavior of the rest of the team members and the constraints are decoupled. In this approach, each agent only shares the future position of itself with the other agents to avoid collisions. For reducing the computation time and complexity, only one step ahead prediction in the corresponding MPC schemes have been considered without a loss of generality. Finally, the e ciency of the overall suggested decentralized MPC scheme, as well as it comparison with the centralized approach, is being evaluated through the utilization of multiple simulation scenarios.

show abstract

UAVs Trajectory Planning by Distributed MPC under Radio Communication Path Loss Constraints

Cited by 55 publications

References 47 publications

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

On corner cutting in multi-obstacle avoidance problems

Distributed model predictive control for unmanned aerial vehicles

Contact Info

Product

Resources

About